Over the last several years, computer aided detection systems have been developed that provide a “second reading” of a medical image such as a mammogram or a chest x-ray. Such systems take a mammogram or x-ray in digital form, process it to locate abnormalities, rank the abnormalities by a scoring algorithm and then display their results in the form of an annotated map that shows the locations of the suspected abnormalities and some measure of their ranking.
The ranking is typically a confidence level that the suspected abnormality is indeed truly an abnormality or a true positive. Alternatively, the ranking could be an estimate of the severity of the suspected abnormality. The ranking can be expressed in numerous ways. For example, it can be expressed numerically alongside a marker indicating the location of the suspected abnormality, or it can be expressed using different size markers for different probability or confidence levels, or different colors, or different shades of the same color. The use of such markers is described, for example, in S. P. Wang's U.S. Pat. No. 6,266,435 for “Computer-Aided Diagnosis Method and System” which is incorporated herein by reference. Examples of commercial use of such markers are found in the assignee's Mammochecker® mammography system and Imagechecker® MSCT system.
As described in the '435 patent, some of the suspected abnormalities will turn out to be of no concern. In other words, they are false positives. Indeed, in any detection system, there is a trade off between sensitivity, or the fraction of true positives detected, and specificity or the fraction of false positives detected. This sensitivity/specificity trade off is often depicted in the detection system's receiver operating characteristic (ROC) curve such as that shown in FIG. 1. The ROC curve is a plot 100 of the fraction of true positives detected (TPF) as measured on the ordinate or y axis versus the fraction of false positives detected (FPF) as measured on the abscissa or x axis. As the fraction of true positives detected (or sensitivity) increases, so does the fraction of false positives detected, thereby decreasing the specificity.
In the medical arts, the trade-off between sensitivity and specificity that is represented by the ROC curve is always a concern. If the detection system is not sensitive enough, it may report too few true positives (i.e., more false negatives) which typically represent missed opportunities to detect some sort of problem that may well be life-threatening. On the other hand, if the detection system is not specific enough, it may report too many false positives which typically will result in the performance of additional medical procedures to establish the true nature of the false positive and, in many cases, considerable emotional stress on the part of the patient. Faced with this trade-off, the medical practitioner is usually forced to set the threshold of his/her detection system by trial-and-error at some value that assures the detection of significant numbers of true positives at the cost of some false positives.
This problem is especially acute in the computer-aided detection (CAD) of lung modules in computer tomography (CT) images. Because large numbers of false positives are present in many CT lung images, it is desirable to permit the medical practitioner to vary the detection threshold. Usually, this is done by entering into the computer system a numerical value. The computer system will then report or mark those inputs that have a score that is in excess of the threshold and will ignore all other events. The number of false positives, however, will vary from one lung image to another and the need to suppress false positives will vary accordingly. Thus, the threshold value required to suppress excess false positives will also vary. In addition, the numerical ranges used in scoring the abnormalities are based on arbitrary scales and will vary from detection system to detection system. The result is that the medical practitioner is often forced into some trial and error process for setting the threshold or is required to consult some other source to determine a suitable threshold.